Enhancing post-fire decision-making: a framework for rapid wildfire impact assessment and evidence-based management planning

Introduction: Altered wildfire regimes, exacerbated by unsustainable management, threaten natural ecosystem recovery post-fire. Effective restoration requires timely fire impact assessments and tailored, evidence-based management. While fire databases and Environmental Impact Assessment (EIA) framew...

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Detalles Bibliográficos
Autores: Cristal, Irina, Puigdemasa, Elena, Palmero Iniesta, Marina, Mauri, Eduard, Pons Ferran, Pere
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2026
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/28270
Acceso en línea:http://hdl.handle.net/10256/28270
Access Level:acceso abierto
Palabra clave:Incendis forestals -- Aspectes ambientals
Forest fires -- Environmental aspects
Boscos -- Gestió
Forest management
Repoblació forestal
Reforestation
Descripción
Sumario:Introduction: Altered wildfire regimes, exacerbated by unsustainable management, threaten natural ecosystem recovery post-fire. Effective restoration requires timely fire impact assessments and tailored, evidence-based management. While fire databases and Environmental Impact Assessment (EIA) frameworks partially support decision-making, a holistic platform linking assessment, planning, and operational actions is still lacking. Objectives: Our goal was to develop and test a web-based Post-Fire Spatial Decision Support System (PF-SDSS) that facilitates decision-making across three post-fire management levels: problem definition, strategic planning, and operational management. Methods: PF-SDSS integrates satellite imagery with high-resolution cartography in a participatory multi-criteria analysis (MCA), using server- and cloud-based computing for real-time analyses. The generated soil erosion risk (SER) and vegetation recovery potential (VRP) maps underpin rule-based restoration prioritization and recommendations that provide site-specific practices derived from a comprehensive literature review. Field validation (Spearman's correlation), sensitivity analysis (MCA weight variations), and usability evaluation (System Usability Scale [SUS] method) assessed the system's performance. Results: PF-SDSS is freely available online, with a demonstration for Ávila Province, Spain. Validation showed significant correlations for SER (ρ = 0.56) and VRP (ρ = 0.42). Sensitivity analysis confirmed MCA robustness under 20% weight variations, and the 75% SUS score indicated satisfactory usability and acceptance among end-users. Conclusions: This study automated the post-wildfire management planning cycle within a modular framework. The EIA module supports problem definition by mapping fire impacts. The strategic planning module identifies priority areas and sets site-specific management objectives. The operational planning module offers spatially oriented, evidence-based management alternatives